Computational Intelligence and Blockchain in Complex Systems System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI machine learning and computational intelligence in blockchain and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications including healthcare insurance smart grid smart contracts digital currency precision agriculture and supply chain The authors cover the unique and developing intersection between cyber security and blockchain in modern networks as well as in depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods especially the complex algorithms involved in blockchain security aspects for hashing coding and decoding This book also provides readers with the most in depth technical guide to the intersection of computational intelligence and blockchain two of the most

This is the only authorized Oracle exam preparation boxed set covering all Database Administration Certification exams, from the creators of Oracle certification book study. Contains four books with more than 2,000 pages of DBA preparation.

Blockchain Technology Solutions for the Security of IoT Based Healthcare Systems explores the various benefits and challenges associated with the integration of blockchain with IoT healthcare systems focusing on designing cognitive embedded data technologies to aid better decision making processing and analysis of large amounts of data collected through IoT This book series targets the adaptation of decision making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and Internet of Things IoT problems can be handled in practice Current Internet of Things IoT based healthcare systems are incapable of sharing data between platforms in an efficient manner and holding them securely at the logical and physical level To this end blockchain technology guarantees a fully autonomous and secure ecosystem by exploiting the combined advantages of smart contracts and global consensus However incorporating blockchain technology in IoT healthcare systems is not easy Centralized networks in their current capacity will be incapable to meet the data storage demands of the incoming surge of IoT based healthcare wearables

Lesen Sie dieses Buch, und sehen Sie der nächsten SAP-Systemprüfung gelassen entgegen! Der Autor zeigt Ihnen, welche Anforderungen Ihr System erfüllen muss und wie Sie ein Internes Kontrollsystem (IKS) einrichten. Dabei lernen Sie, Risiken mithilfe von Kontrollen zu begegnen und die Wirksamkeit dieser Kontrollen zu überprüfen - über alle relevanten Bereiche hinweg. Ausserdem erfahren Sie, wie Sie Ihr IKS automatisieren und ein automatisiertes Test- und Monitoring-Konzept für SAP ERP entwickeln.Sie lernen die gesetzlichen Rahmenbedingungen (z.B. SOX, GoBS, FDA, Datenschutz), Ansätze und Prinzipien eines internen Kontrollsystems (IKS) sowie verschiedene Frameworks (z.B. COSO, CobiT, ITIL u.v.m.) kennen und erfahren, wie SAP Sie bei der Umsetzung dieser Anforderungen und Ansätze unterstützen kann.Anschliessend wird erläutert, wie Sie die IKS-Inhalte in SAP ERP modul- und prozessbezogen umsetzen können.

One consequence of the pervasive use of computers is that most documents originate in digital form. Text miningthe process of searching, retrieving, and analyzing unstructured, natural-language textis concerned with how to exploit the textual data embedded in these documents.Text Mining presents a comprehensive introduction and overview of the field, integrating related topics (such as artificial intelligence and knowledge discovery and data mining) and providing practical advice on how readers can use text-mining methods to analyze their own data. Emphasizing predictive methods, the book unifies all key areas in text mining: preprocessing, text categorization, information search and retrieval, clustering of documents, and information extraction. In addition, it identifies emerging directions for those looking to do research in the area. Some background in data mining is beneficial, but not essential.Topics and features:- Presents a comprehensive and easy-to-read introduction to text mining- Explores the application and utility of the methods, as well as the optimal techniques for specific scenarios- Provides several descriptive case studies that take readers from problem description to system deployment in the real world- Uses methods that rely on basic statistical techniques, thus allowing for relevance to all languages (not just English)- Includes access to downloadable software (runs on any computer), as well as useful chapter-ending historical and bibliographical remarks, a detailed bibliography, and subject and author indexesThis authoritative and highly accessible text, written by a team of authorities on text mining, develops the foundation concepts, principles, and methods needed to expand beyond structured, numeric data to automated mining of text samples. Researchers, computer scientists, and advanced undergraduates and graduates with work and interests in data mining, machine learning, databases, and computational linguistics will find the work an essential resource.

Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.

Texto orientado a un primer curso de bases de datos para los estudios universitarios de Grado. Además del material básico para tal fin, se extiende en algunos epígrafes, pudiendo servir como complemento del curso o como material introductorio de un curso avanzado. Partiendo de un conocimiento elemental de estructuras de datos basicas, organizacion de computadoras y un lenguaje de programacion como Java, C o Pascal, se presentan los conceptos usando descripciones intuitivas, muchas de ellas basadas en el ejemplo propuesto (para toda la obra) de datos de una universidad.

Este best seller recoge todos los últimos desarrollos de la tecnología de bases de datos. Debido a su clara introducción al diseño, implementación y gestión tanto como un extensivo tratamiento de los lenguajes de bases de datos, hace de este manual un texto de referencia, completo e indispensable para cualquier estudiante y profesional.El libro ofrece una clara introduccion al diseño, la implementacion y la gestion, asi como un amplio tratamiento sobre los estandares y los lenguajes de bases de datos, haciendo que sea una referencia completa indispensable para los estudiantes y profesionales de las bases de datos.Los temas complejos se explican de forma clara usando casos de estudio a lo largo de todo el libro.La metodologia de diseño de bases de datos se ha dividido explicitamente en tres fases: conceptual, logica y fisica. Cada fase se describe con un ejemplo de como funciona en la practica.El SQL se cubre de forma exhaustiva en tres capitulos con estilo de tipo tutorial.Se explican en detalle los SGBD distribuidos, orientados a objetos y objeto relacionales.Amplio tratamiento de XML, OLAP y mineria de datos.Se cubren los estandares actualizados, entre los que se incluyen SQL: 2003, W3C (Xpath and XQuery) yOMG.Tambien se cubre Oracle9i y Microsoft Office Access 2003.Este best seller recoge todos los últimos desarrollos de la tecnología de bases de datos. Debido a su clara introducción al diseño, implementación y gestión tanto como un extensivo tratamiento de los lenguajes de bases de datos, hace de este manual un texto de referencia, completo e indispensable para cualquier estudiante y profesional.